Exploiting channel time correlation to reduce channel state information feedback bitrate

ABSTRACT

The required bitrate for reporting channel state information from a network transceiver to the network is dramatically reduced, while maintaining fidelity of channel estimates, by exploiting prior channel estimates and the time correlation of channel response. For a selected set of sub-carriers, the transceiver estimates channel frequency response from pilot signals. The transceiver also predicts the frequency response for each selected sub-carrier, by multiplying a state vector comprising prior frequency response estimate and a coefficient vector comprising linear predictive coefficients. The predicted frequency response is subtracted from the estimated frequency response, and the prediction error is quantized and transmitted to the network. The network maintains a corresponding state vector and predictive coefficient vector, and also predicts a frequency response for each selected sub-carrier. The received prediction error is inverse quantized and subtracted from the predicted frequency response to yield a frequency response corresponding to that estimated at the transceiver.

FIELD OF THE INVENTION

The present invention relates generally to wireless communicationnetworks, and in particular to an efficient system and method fortransmitting channel state information to the network by exploiting thetime correlation of channel response.

BACKGROUND

Wireless communication networks transmit communication signals in thedownlink over radio frequency channels from fixed transceivers, known asbase stations, to mobile user equipment (UE) within a geographic area,or cell. The UE transmit signals in the uplink to one or more basestations. In both cases, the received signal may be characterized as thetransmitted signal, altered by channel effects, plus noise andinterference. To recover the transmitted signal from a received signal,a receiver thus requires both an estimate of the channel, and anestimate of the noise/interference. The characterization of a channel isknown as channel state information (CSI). One known way to estimate achannel is to periodically transmit known reference symbols, also knownas pilot symbols. Since the reference symbols are known by the receiver,any deviation in the received symbols from the reference symbols (onceestimated noise/interference is removed) is caused by channel effects.An accurate estimate of CSI allows a receiver to more accurately recovertransmitted signals from received signals. In addition, by transmittingCSI from the receiver to a transmitter, the transmitter may select thetransmission characteristics—such as coding, modulation, and thelike—best suited for the current channel state. This is known aschannel-dependent link adaptation.

Modern wireless communication networks are interference limited. Thenetworks typically process transmissions directed to each UE in a cellindependently. Transmissions to other UEs in the same cell are regardedas interference at a given UE—giving rise to the term mutualinterference. One approach to mitigating mutual interference ismulti-user multiple input/multiple output (MU-MIMO). With MU-MIMO, asignal to be transmitted to multiple users is formed jointly, and thesetransmissions are formed taking into account the interference thattransmission to one user creates at all other users. To operate mosteffectively, a MU-MIMO transmitter requires information about thetransmission channels to each UE. That is, the transmitter requires CSI.Note that both single-cell MU-MIMO techniques and multi-cell MU-MIMOtechniques can benefit from the availability of CSI at the transmitter.

Even without MU-MIMO transmission, CSI at the network can solve one ofthe most fundamental problems plaguing current wireless system—theinaccuracy in channel-dependent link adaptation due to the network notbeing able to predict the interference experienced by the UEs (a problemclosely related to the well-known flash-light effect). Once the networkknows the CSI of bases near each UE, the network can accurately predictthe SINR at each UE, resulting in significantly more accurate linkadaptation.

Even though the advantages of direct CSI feedback are clear, the majorissue with direct CSI feedback is overhead. Full CSI feedback requires ahigh bitrate to transmit the CSI from each UE to the network.Time-frequency uplink channel resources must be used to carry the CSIfeedback on the uplink channel, making these resources unavailable fortransmitting user data on the uplink—the CSI feedback transmissions arethus pure overhead, directly reducing the efficiency of uplink datatransmissions. Conveying direct CSI feedback to the network withoutconsuming excessive uplink resources stands as a major challenge ofmodern communication system design.

Digital loopback was recently proposed as an efficient means to deliverCSI to the network with reasonable overhead and with quite lowcomplexity. See, e.g., co-pending U.S. patent application Ser. No.12/555,966, filed Sep. 9, 2009, tilted “Efficient Uplink Transmission ofChannel State Information,” assigned to the assignee of the presentapplication and incorporated herein by reference in its entirety. Indigital loopback, a UE transmits succinct, direct channel stateinformation to the network without substantially increasing uplinkoverhead. The UE receives and processes reference symbols over a set ofnon-uniformly spaced sub-carriers, selected according to a schemesynchronized to the network. The frequency response for each selectedsub-carrier is estimated conventionally, and the results areperiodically quantized and transmitted to the network on an uplinkcontrol channel. This is referred to herein as persistent digitalloopback. Based on the information transmitted by the UE on the uplinkchannel, the network is able to construct an estimate of the frequencyresponse of the channel at all sub-carriers, with a certain fidelity fora given bitrate of CSI. Naturally, the higher the bitrate of the CSI,the higher the fidelity of the channel estimation at the network willbe.

SUMMARY

According to one or more embodiments disclosed and claimed herein, CSIreporting bitrate is dramatically reduced, while maintaining fidelity ofchannel estimates communicated to the network, by exploiting priorchannel estimates and the time correlation of channel response. Anetwork transceiver estimates channel frequency response from pilotsignals for a selected set of sub-carriers, as in prior artimplementations of digital loopback. The transceiver also predicts thefrequency response for each selected sub-carrier, by multiplying a statevector comprising prior frequency response estimate and a coefficientvector comprising linear predictive coefficients. The predictedfrequency response is subtracted from the estimated frequency response,and the prediction error is quantized and transmitted to the network.The network maintains a corresponding state vector and predictivecoefficient vector, and also predicts a frequency response, for eachselected sub-carrier. The received prediction error is inverse quantizedand subtracted from the predicted frequency response to yield thefrequency response estimated at the transceiver.

One embodiment relates to an efficient method of reporting CSI by a UEoperative in a wireless communication network in which downlink data ismodulated onto a plurality of sub-carriers, each having a differentfrequency. At each iteration, a plurality of known reference symbols isreceived over a subset of the plurality of sub-carriers. A set ofsub-carriers is selected using a selection scheme synchronized to thenetwork. For each selected sub-carrier, a frequency response isestimated; a frequency response is predicted, in a manner synchronizedto the network, based on prior frequency response estimates and a timecorrelation of channel response; the predicted frequency response issubtracted from the estimated frequency response to yield a predictionerror; and the prediction error is quantized. The quantized predictionerrors for all selected sub-carriers are transmitted to the network viaan uplink control channel.

Another embodiment relates to a method of interpreting CSI by a networknode operative in a wireless communication network in which downlinkdata is modulated onto a plurality of sub-carriers, each having adifferent frequency. At each iteration, quantized prediction errors forselected sub-carriers are received from a network transceiver. For eachselected sub-carrier, the quantized prediction errors are inversequantized; a frequency response is predicted, in a manner synchronizedto the network transceiver, based on prior frequency response estimatesand a time correlation of channel response; and the prediction error isadded to the predicted frequency response to yield a current quantizedfrequency response estimate. The quantized frequency response estimatesfor all selected sub-carriers are used to characterize the downlinkchannel to the network transceiver.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of a wireless communicationnetwork.

FIG. 2 is a functional block diagram of generating Channel StateInformation (CSI) at a network transceiver.

FIG. 3 is a flow diagram of a method of generating CSI at a networktransceiver.

FIG. 4 is a functional block diagram of interpreting CSI at a networknode.

FIG. 5 is a flow diagram of a method of interpreting CSI at a networknode.

FIG. 6 is a graph comparing the performance as a function of bitrate ofinventive CSI reporting to prior art CSI reporting.

DETAILED DESCRIPTION

For the purpose of clear disclosure and full enablement, the presentinvention is described herein as embodied in a wireless communicationnetwork based on Orthogonal Frequency Division Multiplex (OFDM)modulation. More specifically, embodiments herein are based on theEvolved Universal Terrestrial Radio Access (E-UTRA) system, which isalso commonly referred to as the Long-Term Evolution (LTE) of the widelydeployed WCDMA systems. Those of skill in the art will readilyappreciate that these systems are representative only and not limiting,and will be able to apply the principles and techniques of the presentinvention to a wide variety of wireless communication systems, baseddifferent access and modulation methods, given the teachings of thepresent disclosure.

FIG. 1 depicts a wireless communication network 10. The network 10includes a Core Network (CN) 12, communicatively connected to one ormore other networks 14, such as the Public Switched Telephone Network(PSTN), the Internet, or the like. Communicatively connected to the CN12 are one or more Node B stations 18. The Node B 18, also known as abase station, includes radio frequency (RF) equipment and antennasnecessary to effect wireless radio communications with one or more userequipment (UE) 20 within a geographic region, or cell 22. As depicted,the Node B 18 transmits data and control signals to the UE 20 on one ormore downlink channels, and the UE similarly transmits data and controlsignals to the Node B 18 on the uplink.

As described above, in persistent digital loopback, frequency responseestimates for selected sub-carriers are periodically quantized andtransmitted to the network on an uplink control channel. This method ofCSI feedback does not exploit the time correlation of the channel at thereporting intervals. Exploiting this time correlation, embodiments ofthe present invention provide a CSI feedback scheme that can achieve thesame fidelity of persistent digital loopback, but with a lower uplinkbitrate (i.e., lower overhead and hence higher spectral efficiency).

Assume that the UE 20 reports the frequency response of the channel at Msub-carriers every T [seconds], i.e., at times

t=0, T, 2T, 3T, . . .

and denote the frequency response at the m-th reported subcarrier at then-th reporting instance by H(k_(m);n). Furthermore, the time correlationof frequency response at a given subcarrier is denoted by:

ρ_(H)(k;l)=E{H(k;n)H*(k;n−l)}  (1)

Because ρ_(H)(k;l) is non-zero for l not equal to zero, the frequencyresponse at one frequency and two different reporting times can behighly Correlated.

In the persistent digital loopback scheme, the CSI bits associated withH(k;n) that are reported at the n-th reporting instance are generatedindependently from past values of the channel (i.e., Independently ofH(k;n−1), H(k;n−2), H(k;n−3), . . . ). This results in redundancy in theinformation reported to the network.

FIG. 2 is a functional block diagram 30 of an efficient method 100,depicted in FIG. 3 in flow diagram form, of reporting CSI by a UEoperative in a wireless network in which downlink data is modulated ontoa plurality of sub-carriers, each having a different frequency. At eachiteration, or reporting interval, the UE receives a plurality of knownreference symbols over a subset of the plurality of sub-carriers (step102). As known in the art, the reference symbols may be scattered intime and frequency according to a scattered pilot pattern. The UEselects a subset of the sub-carriers, using a selection schemesynchronized to the network (step 104). The sub-carriers may be selectedin numerous ways, as described in co-pending application Ser. No.12/555,966 cited above. The selected sub-carriers are denoted by (k₁,k₂, . . . , k_(M)). Channel conditions are then estimated and predictedfor each selected sub-carrier (step 106), denoted in the followingdiscussion as the m-th selected sub-carrier, denoted k_(m).

The UE 20 estimates the frequency response H(k_(m);t) 32, using knowntechniques (step 108). The UE 20 then predicts a frequency responsevalue r(m;t) 34 for k_(m), based on prior frequency response estimatesand a time correlation of channel response (step 110). The frequencyresponse prediction is generated by a linear predictor 36. Eachpredictor 36 obtains a state vector s_(m)(t) 38 of size L×1, and aprediction coefficient vector w_(m) 40 of size 1×L. The state vectors_(m)(t) 38 is a vector of prior values of quantized frequency responseestimates (as described below) of k_(m). The prediction coefficientvector w_(m) 40 is a vector of linear predictive coefficients based on atime correlation of channel response for k_(m). The state vectors_(m)(t) 38 and prediction coefficient vector w_(m) 40 are multiplied inthe linear predictor 36 to yield the frequency response predictionr(m;t) 34 for k_(m), which is a scalar complex-valued number.

The UE 20 next subtracts the predicted frequency response r(m;t) 34 fromthe estimated frequency response H(k_(m);t) 32 at summer 42, yielding aprediction error e(m;t) 44 (step 112). The real and imaginary parts ofe(k_(m);t) 44 are separately quantized by a quantizer Q_(m)(. ,b_(m)) 46(step 114). The quantizer Q_(m)(. ,b_(m)) 46 has 2^(b) ^(m) quantizationlevels per real part and per imaginary part, and yields quantized bitsb_(m) (t) 48. This process is repeated for all selected sub-carriers(k₁, k₂, . . . , k_(M)) (steps 116, 106)

The quantized bits of all selected sub-carriers are then transmitted viaa suitable control channel from UE 20 to the network 10 (step 118). Asknown in the art, the transmission process may include addingredundancy, such as cyclic redundancy coding (CRC), forward errorcorrection (FEC) coding, and the like, to ensure reliable transmissionto the network 10. The quantized bits, representing the prediction errorfor each selected sub-carrier, comprise significantly less data (andhence uplink overhead) than if the entire estimated frequency responseH(k_(m);t) 32 were transmitted, as is the case in persistent digitalloopback CSI reporting.

An important aspect of embodiments of the present invention is theupdating of the state vector s_(m)(t) 38 for each selected sub-carrier.During each reporting interval, the quantized bits b_(m)(t) 48 reportedto the network 10 are inversely quantized at inverse quantizer 50,yielding the quantized error e_(q)(M;t) 52. This value is added to thepredicted frequency response r(m;t) 34, yielding a quantized frequencyresponse estimate H_(q)(M;t) 54. Note that the quantized frequencyresponse estimate H_(q)(M;t) 54 depends only on the predicted frequencyresponse r(m;t) 34 and the quantized bits b_(m)(t) 48 transmitted to thenetwork 10. The quantized frequency response estimate H_(q)(M;t) 54 isadded to the state vector s_(m)(t) 38, and the oldest value in s_(m)(t)38 is dropped. This processing of the state vector s_(m)(t) 38, and wellas storage, is performed in the state vector update block 56. The statevectors for all selected sub-carriers are updated similarly. The method100 repeats for each reporting interval.

FIG. 3 is a functional block diagram 60 of a method 200, depicted inFIG. 5 in flow diagram form, of interpreting received CSI by a networknode operative in a wireless communication network in which downlinkdata is modulated onto a plurality of sub-carriers, each having adifferent frequency. At each iteration, or reporting interval, thenetwork node, such as a Node B 18, receives quantized prediction errorsb_(m)(t) 61 for a plurality of selected sub-carriers from a networktransceiver, such as a UE 20 (step 202). The selected sub-carriers aredenoted by (k₁, k₂, . . . , k_(M)). Each channel (corresponding to eachselected sub-carrier) is then characterized by the Node B 18. Thisprocess is described for the m-th selected sub-carrier, denoted k_(m),but is repeated for all sub-carriers (step 204).

The Node B 18 inverse quantizes the received quantized prediction errorsb_(m)(t) 61 (step 206), using an inverse quantizer 62 matched to thequantizer 46 used in the UE 20. That is, the inverse quantizer 62 hasthe same quantization levels, and separately inverse quantizes the I andQ components of the received quantized prediction errors, to yieldprediction errors 64.

The Node B 18 then predicts a frequency response value r(m;t) 66 fork_(m), based on prior frequency response estimates and a timecorrelation of channel response (step 208). The frequency responseprediction is generated by a linear predictor 68. Each predictor 68obtains a state vector s_(m)(t) 70 of size L×1, and a predictioncoefficient vector w_(m) 72 of size 1×L. The state vector s_(m)(t) 70 isa vector of prior values of quantized frequency response estimates (asdescribed below) of k_(m). The prediction coefficient vector w_(m) 72 isa vector of linear predictive coefficients based on a time correlationof channel response for k_(m). The state vector s_(m)(t) 70 andprediction coefficient vector w_(m) 72 are multiplied in the linearpredictor 68 to yield the frequency response prediction r(m;t) 66 fork_(m), which is a scalar complex-valued number.

The Node B 18 next adds the predicted frequency response r(m;t) 66 tothe prediction error 64 at summer 74, yielding a current quantizedfrequency response estimate H_(q)(m;t) 76 (step 210). This process isrepeated for all selected sub-carriers (k₁, k₂, . . . , k_(M)) (steps212, 204), generating the vector:

V(t)=[H _(q)(1;t)H _(q)(2;t) . . . H _(q)(M;t)].  (2)

The vector V(t), of quantized frequency response estimates for allselected sub-carriers, is then used to characterize the downlink channelto the UE 20 (step 214), using known signal processing techniques. Forexample, The Node B 18 may estimate the complete frequency domainchannel coefficients by setting a time-domain tap-delay channel modelbased on the quantized frequency response estimates, and apply a FastFourier Transform (FFT) to the estimated delay coefficients to yield afrequency-domain response of the channel. The channel characterizationmay then be used for known procedures, such as removing channel effectsfrom communication signals received from the UE 20, and/or performinglink adaptation for transmissions to the UE 20.

The state vector s_(m)(t) 70 is updated for each selected sub-carrier.During each reporting interval, the quantized channel estimateH_(q)(M;t) 76, which depends only on the predicted frequency responser(m;t) 66 and the prediction error 64 received from the UE 20, is addedto the state vector s_(m)(t) 70, and the oldest value is dropped. Thisprocessing of the state vector s_(m)(t) 70, and well as storage, isperformed in the state vector update block 78. The state vectors for allselected sub-carriers are updated similarly. The method 200 repeats foreach reporting interval.

As noted, the quantized channel estimates H_(q)(M;t) 54, 76 at the UE 20and Node B 18, respectively, depend only on each nodes' predictedfrequency response, and the prediction error generated by the UE 20 andtransmitted to the Node B 18. Each node's frequency response predictionr(m;t) 34, 66, in turn, depend only on the state vectors s_(m)(t) 38, 70and prediction coefficient vectors w_(m) 40, 72. So long as the statevectors s_(m)(t) 38, 70 are initialized and updated in a coordinatedmanner at the UE 20 and Node B 18, the Node B 18 can construct anaccurate estimate of the channel measured by the UE 20, based only onthe received quantized prediction errors b_(m)(t) 48 transmitted by theUE 20 and b_(m)(t) 61 received by the Node B 18 (assuming there are noundetected transmission errors).

In general, at both the state vector update blocks 56 and 78, theupdating of the state vectors s_(m)(t) 38, 70 may be implemented bysetting s_(m)(i;t) (the i-th element of the state of the m-th predictor)to an estimate of the channel at the m-th subcarrier and reporting timeinterval t−i. If the m-th subcarrier remains the same over the maximummemory of the predictor, this value is simply H_(q)(m;t−i). If the m-thsubcarrier changes over the maximum memory of the predictor—that is, theset of sub-carriers selected by the UE 20 for channel estimationchanges—the value s_(m)(i;t) can be obtained by interpolation from theelements of [H_(q)(1;t−i), . . . , [H_(q)(M;t−i)]. This may, forexample, comprise a linear interpolation, or an interpolation accordingto one of the methods outlined in application Ser. No. 12/555,966 citedabove, for reconstruction of the channel at the network from previouslyreported CSI bits.

When a new sub-carrier is added to the set of selected sub-carriers usedfor channel estimation, the states of the predictors for thissub-carrier at the UE 20 and the Node B 18 (or other network 10 node)should be synchronized. The synchronization can be accomplished byapplying identical update rules, as disclosed above, at the UE 20 andthe Node B 18. This has the advantage of not consuming additional radioresources to exchange information between the UE 20 and the Node B 18.Alternatively, when different updating methods are implemented at the UE20 and the Node B 18, auxiliary information is exchanged between the twoentities to synchronize the predictor states.

In one embodiment, the Node 18 (or other network 10 node) may commandthe UE 20 to add or remove a sub-carrier from its set of selectedsub-carriers for CSI feedback. The Node B 18 may make the decision onthe addition or removal of sub-carriers, for example, based on a changein the channel delay profile measured in the reverse link, in order toproperly populate the selected sub-carriers, or based on a predefinedpseudo-random selection. Methods and arrangements for such synchronizedreporting sub-carrier sets are taught in application Ser. No. 12/555,966cited above.

Once a new sub-carrier is added to the selected set, and following thesynchronization of the states of the predictors at the UE 20 and theNode B 18 for the new subcarrier, the UE 20 preferably continuesreporting CSI on this sub-carrier at every subsequent reportinginstance, until this subcarrier is dropped from the selected set ofsubcarriers.

In one embodiment, the quantizers 46 for all the selected sub-carriershave the same parameters (i.e., the same number of bits, and the samequantization levels). This follows from the non-trivial observation thatequation (1), reproduced below

ρ_(H)(k;l)=E{H(k;n)H*(k;n−l)}  (1)

is the same for all subcarriers “k”. This implies that the timecorrelation of H(k,n) is the same for all subcarriers “k”. With thisobservation, only one set of quantizer parameters needs to be exchangedbetween the UE 20 and the Node B 18. This also has implications for thepredictors, as discussed in greater detail below.

In one embodiment, the quantization levels of the quantizer 46 used bythe UE 20 for each selected sub-carrier is the optimal (i.e., minimumdistortion) quantizer corresponding to an input to a quantizer with azero-mean Gaussian probability distribution function and having varianceequal to the variance of the real part of prediction error e(m;t) 44 inFIG. 2. In one embodiment, the variance of the real part (or theimaginary part) of the input to the quantizer 46 in FIG. 2 iscommunicated from the UE 20 to the Node B 18 on slow a basis.

In one embodiment, the quantization levels of the quantizer 46 used atthe UE 20 are derived from the variance of the real part (or imaginarypart) of e(m;t) 44 according to an algorithm known to both the UE 20 andthe Node B 18. For example, one appropriate algorithm is the Lloyd-Maxalgorithm described in a paper by S. P. Lloyd, titled “Least SquaresQuantization in PCM,” published as Bell Laboratories Technical Note,1957, the disclosure of which is incorporated herein by reference in itsentirety. In this manner, the Node B 18 is able to form the inversequantizer 62 associated with the quantizer 46 used by the UE 20 from theknowledge of the variance of the real part (or imaginary part) of e(m;t)44 alone. This avoids the necessity for the UE 20 to communicatemultiple quantization levels to the Node B 18.

In one embodiment, the prediction coefficients comprising the predictioncoefficient vectors w_(m) 40, 72 for all the selected subcarriers arethe same. This again follows from the above non-trivial observation thattime correlation of H(k;n), see equation (1), is the same for allsubcarriers “k”. With this observation, only one set of predictorcoefficients needs to be exchanged between the UE 20 and the Node B 18.In one embodiment, the predictor coefficients used at the UE 20 arecommunicated from the UE 20 to the Node B 18 on slow basis.

Embodiments described herein significantly reduce CSI feedback overheadcompared with the prior art technique of persistent digital loopback asdescribed in application Ser. No. 12/555,966 cited above, while enablinghighly accurate CSI availability to the network. Simulations wereconducted to compare and quantify this performance improvement. Theenvironment simulated is the 3GPP SCM Case 3 channel (see 3GPP TechnicalSpecification TR 25.996, incorporated herein by reference in itsentirety) with two transmit antennas at the Node B 18 and with onereceive antenna at the UE 20. A UE 20 speed of 3 kmph, and carrierfrequency of 2 GHz, were selected.

FIG. 6 depicts the performance of persistent digital loopback andembodiments of the present invention, in terms of reconstruction SNR atthe network versus the bitrate required for CSI feedback. Note that inboth cases, as the bitrate devoted to CSI increases, the reconstructionaccuracy improves (higher SNR). However, a given level of reconstructionSNR is consistently reached in embodiments of the present invention at abit rate well below that required for comparable performance usingpersistent digital loopback. For example, for a reconstruction accuracyof 19 dB, the existing digital loopback scheme requires 3.3 kbpsfeedback. The same performance using embodiments of the presentinvention requires only 1.8 kbps of CSI feedback. This example showsthat embodiments of the present invention can reduce the CSI bitrate byapproximately 45%. The improvement at higher reconstruction SNR is evenmore dramatic.

The present invention may, of course, be carried out in other ways thanthose specifically set forth herein without departing from essentialcharacteristics of the invention. The present embodiments are to beconsidered in all respects as illustrative and not restrictive, and allchanges coming within the meaning and equivalency range of the appendedclaims are intended to be embraced therein.

1. An efficient method of reporting channel state information (CSI) by atransceiver operative in a wireless communication network in whichdownlink data is modulated onto a plurality of sub-carriers, each havinga different frequency, comprising, at each iteration: receiving aplurality of known reference symbols over a subset of the plurality ofsub-carriers; selecting a set of sub-carriers using a selection schemesynchronized to the network; for each selected sub-carrier, estimating afrequency response; predicting a frequency response, in a mannersynchronized to the network, based on prior frequency response estimatesand a time correlation of channel response; subtracting the predictedfrequency response from the estimated frequency response to yield aprediction error; quantizing the prediction error; and transmitting thequantized prediction errors for all selected sub-carriers to the networkvia an uplink control channel.
 2. The method of claim 1 wherein thesub-carriers in the selected set are non-uniformly spaced in frequency.3. The method of claim 1 wherein predicting a frequency response basedon prior frequency response estimates comprises: maintaining a statevector comprising prior values of quantized frequency response estimatesof the selected sub-carrier; generating a coefficient vector comprisinglinear predictive coefficients based on a time correlation of channelresponse; and multiplying the state vector by the coefficient vector toyield a scalar complex-valued frequency response prediction.
 4. Themethod of claim 3 wherein the predictive coefficients for allsub-carriers in the set of selected sub-carriers are the same.
 5. Themethod of claim 3 wherein the sub-carrier was in the set of selectedsub-carriers during the preceding CSI reporting interval, and furthercomprising updating the state vector by: adding the quantized predictionerror to the predicted frequency response to yield a current quantizedfrequency response estimate; appending the current quantized frequencyresponse estimate to the state vector; and removing the oldest quantizedfrequency response estimate from the state vector.
 6. The method ofclaim 3 wherein the sub-carrier is newly added to the set of selectedsub-carriers for the current CSI reporting interval, and whereinmaintaining a state vector comprising prior values of quantizedfrequency response estimates of the selected sub-carrier comprises:interpolating between values for the current CSI reporting interval ofstate vectors associated with the nearest flanking sub-carriers thatwere in the set of selected sub-carriers for the preceding CSI reportinginterval; creating a new state vector for the sub-band; and initializingthe new state vector with the interpolated value.
 7. The method of claim6 further comprising removing a state vector associated with asub-carrier removed from the set of selected sub-carriers for thecurrent CSI reporting interval.
 8. The method of claim 1 whereinquantizing the prediction error comprises separately quantizing the realand imaginary parts of the prediction error using a quantizer havingpredetermined quantization levels.
 9. The method of claim 8 wherein thequantizer and quantization levels are synchronized to the network. 10.The method of claim 9 wherein the quantization levels of the quantizeris the minimum distortion quantizer corresponding to an input to aquantizer with a zero-mean Gaussian probability distribution functionand having variance equal to the variance of one of the real orimaginary part of the prediction error.
 11. The method of claim 9wherein the quantization levels of the quantizer are derived from thevariance of one of the real or imaginary part of the prediction erroraccording to an algorithm used at both the UE and the network.
 12. Themethod of claim 11 wherein the algorithm is a Lloyd-Max algorithm. 13.The method of claim 1 wherein selecting a set of sub-carriers using aselection scheme synchronized to the network comprises adding orremoving a sub-carrier from a set of selected sub-carriers in responseto a direction from the network.
 14. A transceiver operative in awireless communication network in which downlink data is modulated ontoa plurality of sub-carriers, each having a different frequency,comprising: one or more antennas; a transceiver operatively connected tothe antenna(s) and operative to receive a plurality of known referencesymbols over a subset of the plurality of sub-carriers; a controlleroperative to select a set of sub-carriers using a selection schemesynchronized to the network; for one or more selected sub-carriers, afrequency response estimator operative to estimating a frequencyresponse; a linear predictor operative to predict a frequency response,in a manner synchronized to the network, based on prior frequencyresponse estimates and a time correlation of channel response; a summeroperative to subtract the predicted frequency response from theestimated frequency response to yield a prediction error; and aquantizer operative to quantize the prediction error; and wherein thetransmitter is further operative to transmit channel state information(CSI) in the form of quantized prediction errors for all selectedsub-carriers to the network via an uplink control channel;
 15. Thetransceiver of claim 14 further comprising: an inverse quantizer,matched to the quantizer, operative to inverse quantize the quantizedprediction error; and a summer operative to add the inverse quantizedprediction error to the predicted frequency response to yield aquantized frequency response estimate.
 16. The transceiver of claim 15further comprising a state vector update block operative to store andmaintain a state vector comprising prior values of quantized frequencyresponse estimates for each selected sub-carrier.
 17. A method ofinterpreting channel state information (CSI) by a network node operativein a wireless communication network in which downlink data is modulatedonto a plurality of sub-carriers, each having a different frequency,comprising, at each iteration: receiving quantized prediction errors forselected sub-carriers from a network transceiver; for each selectedsub-carrier, inverse quantizing the quantized prediction errors;predicting a frequency response, in a manner synchronized to the networktransceiver, based on prior frequency response estimates and a timecorrelation of channel response; adding the prediction error to thepredicted frequency response to yield a current quantized frequencyresponse estimate; and using the quantized frequency response estimatesfor all selected sub-carriers to characterize the downlink channel tothe network transceiver.
 18. The method of claim 17 further comprisingremoving channel effects from one or more communication signals receivedfrom the network transceiver, based on the downlink channelcharacterization.
 19. The method of claim 17 further comprisingperforming link adaptation for transmissions to the network transceiver,based on the downlink channel characterization.
 20. The method of claim17 wherein using the quantized frequency response estimates for allselected sub-carriers to characterize the downlink channel comprises:estimating the complete frequency domain channel coefficients by settinga time-domain tap-delay channel model based on the quantized frequencyresponse estimates; and applying a Fast Fourier Transform to theestimated delay coefficients to yield a frequency-domain response of thechannel.
 21. A network node in a wireless communication network in whichdownlink data is modulated onto a plurality of sub-carriers, each havinga different frequency, comprising: one or more antennas; a receiveroperatively connected to the antenna(s) and operative to receivequantized prediction errors for selected sub-carriers from a networktransceiver; for one or more selected sub-carriers, an inverse quantizermatched to a corresponding quantizer in the network transceiver andoperative to inverse quantize the received quantized prediction errors;a linear predictor operative to predict a frequency response, in amanner synchronized to the network transceiver, based on prior frequencyresponse estimates and a time correlation of channel response; and asummer operative to add the inverse quantized prediction errors to thepredicted frequency response to yield a quantized frequency responseestimate.
 22. The network node of claim 21 further comprising a statevector update block operative to store and maintain a state vectorcomprising prior values of quantized frequency response estimates foreach selected sub-carrier.